Universidad Católica San Antonio de Murcia (UCAM)

Universidad Católica San Antonio de Murcia (UCAM)
Address:  Campus de los Jerónimos, s/n. 30107 Guadalupe (Murcia)
Country: Spain
Bioinformatics and High Performance Computing Research Group
Principal Investigator: Horacio Pérez-Sánchez, PhD

Institution Background

 Strategically located in Murcia (Spain) with a Campus of 15.700 students and around 1.000 professors, UCAM is a private Catholic University with sixteen years of history which offers 26 prominent European official degrees studies, 45 Master programmes and 17 PhD programmes, among other relevant studies. Its teaching method is based on a personalized attention with reduced students per classes and a personal tutor for each student. UCAM also offers a modern system of distance teaching. With a strong international vocation, UCAM students have the opportunity to develop their global perspective thanks to the joint programs, scientific collaborations and exchange agreements with more than 160 universities all around the world, including UC Berkeley, UC Stanford, Università di Bologna, National University of Singapore (NUS), Nanyang Technological University (NTU), PUC – Rio Grande do Sul,
Wuhan University & Beijing Foreign Studies University.


Research Group Background

Our multidisciplinary research group (http://bio-hpc.eu) is based at Universidad Católica San Antonio de Murcia (UCAM, South East Spain). We work in the exploitation of High Performance Computing Architectures (Supercomputers, GPUs) for the development, acceleration and application of bioinformatics applications, and  we deliver and apply an improved integrated computational-experimental strategy for the discovery of bioactive compounds with desired functional properties.


Major Interest in Action Scientific Topics

Current processors are endowed with many simpler processors, having a tremendous potential in terms of peak performance. Moreover, emergent platforms such as Graphics Processing Units (GPUs), the Field Programmable Gate Array (FPGAs), Accelerating Processing Units (APUs), etc. have been consolidated for developing scientific applications in different areas including bioinformatics, finance, seismic processing, fluid dynamics, etc. However, it is not a trivial task to take advantage of the peak performance that these platforms provide to the scientific community. We are therefore interested in benchmarking these emergent architectures in terms of both: performance and power consumption and to use them to solve relevant problems within the field of Bioinformatics.